Spatio-Temporal Kriging for Monthly Precipitation Interpolation in East Kalimantan
Abstract
Precipitation is one of the factors that can lead to various disasters, such as droughts and floods. Ordinary interpolation methods, such as spatial kriging, cannot accommodate the time element, which is crucial for addressing precipitation-related disasters. Therefore, this study applies a spatio-temporal kriging, which incorporates both spatial and temporal elements. The aim of this study is to develop a spatio-temporal kriging model for precipitation, serving as a basis for interpolating precipitation at unobserved points over various time intervals within the study domain. This model is expected to be an effective tool for disaster mitigation and water conservation strategies. The data used in this study comprises total monthly precipitation recorded at seven precipitation observation posts in East Kalimantan from 2021 to 2023. The findings indicate that the spatio-temporal ordinary kriging model is the most suitable approach, with the best semivariogram model identified as the simple sum-metric. The spatial semivariogram follows an exponential model, while the temporal and joint semivariograms follow Gaussian models. The accuracy of the chosen model yields an RMSE of 2493.687. The interpolation results reveal that West Kutai falls within the medium to high precipitation category, making it the district with the highest flood risk.
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DOI: http://dx.doi.org/10.12962%2Fj27213862.v8i2.22195
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